Implementation of digital MemComputing using standard electronic components

TL;DR

This paper presents a practical hardware implementation of digital MemComputing machines using standard electronic components, achieving faster computation and greater noise robustness compared to simulation-based models.

Contribution

The study introduces a novel hardware design for DMMs with common electronic parts, enhancing speed and stability over previous simulation-based approaches.

Findings

Significantly increased computational speed

High robustness against additive noise

Enhanced stability during long-term operation

Abstract

Digital MemComputing machines (DMMs), which employ nonlinear dynamical systems with memory (time non-locality), have proven to be a robust and scalable unconventional computing approach for solving a wide variety of combinatorial optimization problems. However, most of the research so far has focused on the numerical simulations of the equations of motion of DMMs. This inevitably subjects time to discretization, which brings its own (numerical) issues that would be otherwise absent in actual physical systems operating in continuous time. Although hardware realizations of DMMs have been previously suggested, their implementation would require materials and devices that are not so easy to integrate with traditional electronics. Addressing this, our study introduces a novel hardware design for DMMs, utilizing readily available electronic components. This approach not only significantly boosts computational speed compared to current models but also exhibits remarkable robustness against additive noise. Crucially, it circumvents the limitations imposed by numerical noise, ensuring enhanced stability and reliability during extended operations. This paves a new path for tackling increasingly complex problems, leveraging the inherent advantages of DMMs in a more practical and accessible framework.